The ancient city of Chersonesos created an agricultural zone in the 4th and 3rd centuries BC (under the conditions of climate aridization); this zone was initially used for viticulture and the export of wine, and grain farming later developed at the distant chora (in North-Western (NW) Crimea). The purpose of our work was to verify whether the ampeloecological conditions, especially the geochemical features of the soil and rock, limited viticulture in NW Crimea. Fallow lands in 13 plots in the near and distant chora of Chersonesos were studied using ampelopedology; specifically, we compared agrochemical properties and the concentrations of macro- and trace elements in the renaturation soil horizon and in the parent rock. The main differences between the soils of the two regions were determined by the accumulation of cinnamonic soils of Chersonesos Si, K, Fe, Al, P2O5; in the distant chora, there are specific elements, including V, Pb, Rb, Cr. The climate and the biogeochemical diversity of soils and rock could be significant factors causing the differences in wine quality in the two regions of western Crimea; these factors are still reflected in modern viticultural practices when using the concept of “terroir”. These findings are consistent with the different roles of ancient viticulture in SW (South-Western) and NW (North-Western) Crimea (i.e., export and local consumption, respectively), which have been highlighted by historians.
Background: Several studies have concentrated on finding a combination of predictive parameters to establish a mathematical model that can identify patients with no axillary metastasis for whom routine lymph node dissection could be safely avoided. We developed a new model of nomogram (the Ulyanovsk Cancer Center axillary lymph node metastasis nomogram, UCC-ALNM nomogram); it employs clinically and pathologically relevant variables and offers possible advantages over the others nomograms.
The purpose of the study: To assess the predictive power of UCC-ALNM nomogram.
Methods: A total of 530 breast cancer patients treated between 2008 and 2010 were used as the modeling group for validating the UCC-ALNM nomogram. Clinical and pathologic features of patients were assessed by multivariable logistic regression to predict the presence of axillary metastasis in breast cancer patients. The predictive accuracy of our nomogram was measured by calculating the area under the receiver-operating characteristic (ROC) curve (AUC). Clinical factors included into analysis were: patient’s age and localization of the primary tumor. Pathological factors evaluated were: traditional pathological criteria (primary tumor size, histological type, tumor grade, HR- and Her-2 status) and new total pathological index (Ulyanovsk prognostic index - UPI), introduced by pathologists of the Ulyanovsk Regional Cancer Center. UPI is total score of six main pathological criteria that characterize the malignancy of epithelial tumors: degree of cellular differentiation, cellular polymorphism, mitotic activity, growth pattern, lymphovascular invasion, stromal reaction.
Results: By the multivariate analysis, patient’s age (p=0.04), tumor size (p<0.001), UPI (p<0.001), PR (p<0.001) and Her2 status (p=0.02) were identified as independent predictors of axillary metastasis. The nomogram was then developed using the six variables associated with axillary metastasis: age, tumor size, PR, Her2, UPI.
The new model was accurate and discriminating with an AUC of 0.7510 when applied to the modeling group.
Conclusions: UPI is a new predictive factor of axillary metastasis in breast cancer patients. UCC-ALNM nomogram.
Citation Format: Valery Rodionov, Vlada Cometova, Sergey Panchenko, Sereda Idrisova, Yurij Savinov, Maria Rodionova. A new nomogram to predict axillary metastasis in breast cancer patients without axillary surgery [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P2-01-30.
Informative capacity analysis of immunohistochemistry (IHC) and flow cytometry (FCM) in the assessment of estrogen receptor α (ERα) expression in breast cancer tissue was performed. Similar frequencies of expression were shown by both methods: 27% of ERα-negative and 73% ERα-positive cases. However, IHC evaluation detected low levels in only 20% of ERα-positive cases, whereas low levels of ERα detected by FCM were 2 times more often (48%). Moreover, FCM revealed positive expression (23-60%) in 33% of IHC ERα-negative cases. Among IHC ER-positive cases, zero ERα expression was detected by FCM in 12.5%. The approaches to minimize errors in routine clinical determination of the estrogen receptor status were proposed.
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